Human genetic information is encoded in long strands of DNA that are folded into an organized and highly conserved structure within each cell's nucleus. The resulting three-dimensional structure is thought to play a major role in the regulation of gene transcription and biological processes. However, the mechanisms controlling 3D nucleome structure and the biological impacts thereof remain poorly understood. Poor sensitivity and inaccurate computational tools have limited our ability to characterize the dynamics of 3D chromatin structure over biological time courses. Such 4D studies (time being the fourth dimension) are critical for our understanding of the impacts of 3D structure as they allow for the establishment of causal relationships between long-range interactions and changes in gene expression. This proposal describes improved methods to generate and analyze ChIA-PET data sets as well as their application to study dynamic biological processes. The improved protocol, transposase-aided ChIA-PET (T-ChIA-PET), introduces just a single protocol change that decreases sample handling, increases the efficiency of library generation, and gives rise to longer more `alignable' DNA fragments. Novel software to process ChIA-PET and T-ChIA-PET experiments is proposed that accurately detects interactions by jointly modeling the effect of genomic distance and peak depth on interaction frequency. In combination these improvements will reduce required cell input, increase the fraction of usable reads per experiment, and increase the accuracy of detected interactions. These methods will be employed in combination with ChIP-Seq, RNA-Seq, and ATAC-Seq to characterize changes in chromatin conformation over biologically relevant time courses including response to bacterial infection and progression through the cell cycle. Integrating results from the ChIA-PET and ChIP-Seq experiments will provide mechanistic insight into how different subunits of cohesion contribute to chromatin conformation. Combining ChIA-PET, ATAC-Seq, and RNA-Seq data will reveal the regulatory impacts of chromatin looping events and allow for the construction of detailed and testable models of long-range transcriptional regulation. These experiments will overcome current methodological limitations, increase our knowledge regarding 3D chromatin structure, and provide a solid foundation on which to build a successful research program aimed at deconstructing the role of chromosomal interactions in human disease and development.